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domain-transfer-net's Issues

emoji data

我这里有部分自己爬取的表情数据,是UNSUPERVISED CROSS-DOMAIN IMAGE GENERATION
论文中所用到的,如果你需要,可以联系我。我是否可以向你请教,跨域转换网络你怎么实现的。

digit transfer

Hi
Could you tell me how to run the digit transfer code ? the detail steps introduction,thanks.

Generating duplicates when using datasets/create_emojis_parallel.py

The issue is because every process has the same state for generating random integers and it ends up creating duplicates of emojis.
Fix:
Change pool.map from:

pool.map(create_emoji, range(0, num_emojis))

to:

pool.map(create_emoji, random.randint(0,num_emojis,num_emojis))

And set random.seed(i) at the beginning of function create_emoji()

Missing train_data_info.txt for MSCeleb1MDataset

I got an error during executing the notebook, when I tried to execute test.create_data_loaders()

image

It seems that I'm missing train_data_info.txt in the ms-celeb-1m data directory, while there's only test_data_info.txt being generated by decode_image.py

How should I get this file?

how to

how to run code from svhn to mnist,I run all your python file ,there is no effect.

cuncun @ amax in ~/domain-transfer-net on git:master x [19:26:13]

$ python digit_model_test.py

cuncun @ amax in ~/domain-transfer-net on git:master x [19:26:33]

$ python data.py

cuncun @ amax in ~/domain-transfer-net on git:master x [19:27:12]

$ python classifier_f_test.py

Emoji generation of a specific face

As in the research paper mentioned, how does it generate an emoji of a specific face? Basically, does it generate an emoji for a given face?

Which faces_model is it referring to?

I'm currently trying your notebook, and on the first cell I got error on this line

from faces_model_test import FaceTest

I assume this line trying to your training script, but which does it actually target? Because you have face_model_test_open and face_model_test_sphere

the result of emoji training is not well

I run Begin Model Testing in FaceMain.ipynb , each training openface and sphere 100 epoch . the result of image can't generate emoji and show nothing ,loss function does not converge .

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